{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T05:14:38Z","timestamp":1776489278747,"version":"3.51.2"},"reference-count":19,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2014,7,8]],"date-time":"2014-07-08T00:00:00Z","timestamp":1404777600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Theoretical analysis in this paper indicates that the accuracy of a silicon piezoresistive pressure sensor is mainly affected by thermal drift, and varies nonlinearly  with the temperature. Here, a smart temperature compensation system to reduce its effect on accuracy is proposed. Firstly, an effective conditioning circuit for signal processing and data acquisition is designed. The hardware to implement the system is fabricated. Then, a program is developed on LabVIEW which incorporates an extreme learning machine (ELM) as the calibration algorithm for the pressure drift. The implementation of the algorithm was ported to a micro-control unit (MCU) after calibration in the computer. Practical pressure measurement experiments are carried out to verify the system\u2019s performance. The temperature compensation is solved in the interval from \u221240 to 85 \u00b0C. The compensated sensor is aimed at providing pressure measurement in oil-gas pipelines. Compared with other algorithms, ELM acquires higher accuracy and is more suitable for batch compensation because of its higher generalization and faster learning speed. The accuracy, linearity, zero temperature coefficient and sensitivity temperature coefficient of the tested sensor are 2.57% FS, 2.49% FS, 8.1 \u00d7 10\u22125\/\u00b0C and 29.5 \u00d7 10\u22125\/\u00b0C before compensation, and are improved to 0.13%FS, 0.15%FS, 1.17 \u00d7 10\u22125\/\u00b0C and 2.1 \u00d7 10\u22125\/\u00b0C respectively, after compensation. The experimental results demonstrate that the proposed system is valid for the temperature compensation and high accuracy requirement of  the sensor.<\/jats:p>","DOI":"10.3390\/s140712174","type":"journal-article","created":{"date-parts":[[2014,7,8]],"date-time":"2014-07-08T11:15:26Z","timestamp":1404818126000},"page":"12174-12190","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":83,"title":["A Smart High Accuracy Silicon Piezoresistive Pressure Sensor Temperature Compensation System"],"prefix":"10.3390","volume":"14","author":[{"given":"Guanwu","family":"Zhou","sequence":"first","affiliation":[{"name":"State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, No. 28, Xianning West Road, Xi'an 710049, China"}]},{"given":"Yulong","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, No. 28, Xianning West Road, Xi'an 710049, China"}]},{"given":"Fangfang","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, No. 28, Xianning West Road, Xi'an 710049, China"}]},{"given":"Wenju","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, No. 28, Xianning West Road, Xi'an 710049, China"}]}],"member":"1968","published-online":{"date-parts":[[2014,7,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1109\/JPROC.2009.2013612","article-title":"Review: Semiconductor piezoresistance for microsystems","volume":"97","author":"Barlian","year":"2009","journal-title":"Proc. IEEE"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1088\/0964-1726\/6\/5\/004","article-title":"Micromachined pressure sensors: Review and recent developments","volume":"6","author":"Eaton","year":"1997","journal-title":"Smart Mater. Struct."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.phpro.2011.10.008","article-title":"The thermal drift characteristics of piezoresistive pressure sensor","volume":"21","author":"Otmani","year":"2011","journal-title":"Phys. Procedia"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/S0924-4247(97)80121-5","article-title":"Theoretical model of performance of a silicon piezoresistive pressure sensor","volume":"57","author":"Perraud","year":"1996","journal-title":"Sens. Actuators A Phys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1088\/0022-3735\/16\/10\/003","article-title":"Sensors for microprocessor-based applications","volume":"16","author":"Brignell","year":"1983","journal-title":"J. Phys. E Sci. Instrum."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1023\/A:1004168614028","article-title":"Correction of a piezoresistive pressure sensor using a microcontroller","volume":"44","year":"2001","journal-title":"Instrum. Exp. Tech."},{"key":"ref_7","first-page":"74","article-title":"An LTCC-based capacitive pressure sensor with a digital output","volume":"40","author":"Santo","year":"2010","journal-title":"Inf. MIDEM"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1109\/19.863933","article-title":"An intelligent pressure sensor using neural networks","volume":"49","author":"Patra","year":"2000","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/S0019-0578(99)00035-X","article-title":"Modeling of an intelligent pressure sensor using functional link artificial neural networks","volume":"39","author":"Patra","year":"2000","journal-title":"ISA Trans."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/j.microrel.2005.04.008","article-title":"Temperature compensation of piezoresistive micro-machined porous silicon pressure sensor by ann","volume":"46","author":"Pramanik","year":"2006","journal-title":"Microelectron. Reliab."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.microrel.2009.09.012","article-title":"Ann based cmos asic design for improved temperature-drift compensation of piezoresistive micro-machined high resolution pressure sensor","volume":"50","author":"Futane","year":"2010","journal-title":"Microelectron. Reliab."},{"key":"ref_12","unstructured":"Chen, G., Sun, T., Wang, P., and Sun, B. (June, January 28). Design of temperature compensation system of pressure sensors. Chengdu, China."},{"key":"ref_13","unstructured":"Systems, M.M.I. (2006). Absolute Integrated Pressure Sensor; Melexis Microelectronic Integrated Systems. MLX90269 Datasheet, [Rev. 0.02]."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.sna.2003.07.011","article-title":"A novel high temperature pressure sensor on the basis of soi layers","volume":"108","author":"Zhao","year":"2003","journal-title":"Sens. Actuators A Phys."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"8349","DOI":"10.3390\/s91008349","article-title":"Microgyroscope temperature effects and compensation-control methods","volume":"9","author":"Xia","year":"2009","journal-title":"Sensors"},{"key":"ref_16","unstructured":"Lee, Y.-T., Seo, H.-D., Kawamura, A., Yamada, T., Matsumoto, Y., Ishida, M., and Nakamura, T. (1995, January 25\u201329). Compensation method of offset and its temperature drift in silicon piezoresistive pressure sensor using double wheatstone-bridge configuration. Stockholm, Sweden."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","article-title":"Extreme learning machine: Theory and applications","volume":"70","author":"Huang","year":"2006","journal-title":"Neurocomputing"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"27:1","DOI":"10.1145\/1961189.1961199","article-title":"Libsvm: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_19","unstructured":"Junhua, L. (2010). Intelligent Sensor System, Xidian University Publisher. [2nd ed.]."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/7\/12174\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:13:25Z","timestamp":1760217205000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/7\/12174"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,7,8]]},"references-count":19,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2014,7]]}},"alternative-id":["s140712174"],"URL":"https:\/\/doi.org\/10.3390\/s140712174","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,7,8]]}}}